Search

A combination of field data and models have been used to estimate long-term carrying capacity (LTCC) of domestic livestock in Queensland grazing lands. These methods have been synthesised and coupled with recent developments in science and information technology to provide a fully-automated approach of modelling LTCC through the FORAGE online system. In this study, the GRASP model was used to simulate pasture growth with parameter sets and safe pasture utilisation rates defined for 225 land types across Queensland. Distance to water points was used to assess the accessibility of pastures to livestock. Spatial analysis classified the property into unique areas based on paddock, land type and distance to water points, which estimated pasture growth, pasture utilisation and accessibility at a sub-paddock scale. Thirteen foliage projective cover (FPC) classes were used in modelling the pasture system to deal with the non-linear relationship between tree and grass interactions. As ‘proof of concept’, remotely-sensed individual-date green ground cover data were used to optimise the GRASP model parameters to improve the model performance, and a Monte Carlo analysis provided uncertainty estimates for model outcomes. The framework provides an efficient and standardised method for estimating LTCC. To test the system, LTCCs from 43 ‘benchmark’ properties were compared with simulated LTCCs, and 65% of the modelled LTCCs were within ± 25% of the benchmark LTCCs. Due to uncertainties in model inputs at the property scale and in model simulation, the modelled LTCC should be used as a starting point for further refinement of actual property LTCC.

This paper (Part 1) describes the development of a new online system that estimates long-term carrying capacity (LTCC) for grazing properties across Queensland, Australia. High year-to-year and multi-year rainfall variability is a dominating feature of the climate of Queensland’s grazing lands, and poses major challenges for extensive livestock production. The use of LTCC is one approach used by graziers to reduce the impact of rainfall variability on land condition and financial performance. Over the past 30 years, scientists, graziers and their advisors have developed a simple approach to calculating LTCC ((average annual pasture growth × safe pasture utilisation) ÷ annual animal intake). This approach has been successful at a property scale (regional south-west Queensland) and in a wider application through Grazing Land Management (GLM) regional workshops. We have built on these experiences to develop an online system (as described in detail in Part 2; Zhang et al. 2021; this issue) that incorporates the simple LTCC approach with advances in technology and grazing science to provide LTCC information for Queensland grazing properties. Features of the LTCC system are: (1) assimilation of spatial datasets (cadastral data, grazing land types, climate data, remotely-sensed woody vegetation cover); (2) a pasture growth simulation model; (3) land type parameter sets of biophysical attributes; and (4) estimates of safe pasture utilisation. The ‘FORAGE LTCC report’ is a major product of the system, describing individual property information that allows detailed analysis and explanation of the components of the LTCC calculation by land type and land condition. The online system rapidly analyses property spatial data and calculates paddock/property LTCC information. For the 10 months between November 2020 and August 2021, over 4000 grazing property reports have been requested in Queensland, and has proven to be a sound basis for ‘discussion support’ with grazier managers and their advisors.

Year-to-year variability in rainfall has long been recognised as a major issue in managing livestock enterprises across Australia’s grazing lands. Extension products documenting rainfall variability have been developed over the last 30 years and have been keenly sought by producers and their advisors. This paper describes multi-year rainfall variability from 1889 to 2020 and provides the basis for classifying the 131 years of rainfall into 18 discrete Wet (7), Average (2) and Dry (9) periods as presented in the ‘Queensland’s Extended Wet and Dry Periods’ poster. The classification was consistent with: analysis of fluctuations and trends in the long-term time series of reported livestock numbers; drought declarations for government assistance; and documented periods of pasture resource degradation and recovery. Rainfall during the nine Wet and Average periods was +18% above the long-term average annual rainfall (LTAAR), in contrast to the Dry periods with −17% below LTAAR. Wet periods (including Average) were on average 7 years in duration, ranging from 5 to 9 years. Dry periods were on average 8 years in duration and ranged from 5 to 13 years. Detailed analysis of the effects of the El Niño Southern Oscillation (ENSO) phenomenon indicated that: (a) the Wet/Dry periods were dominated by different frequencies and amounts of rainfall in La Niña/El Niño years; (b) rainfall in ENSO neutral years was generally above and below average rainfall for the Wet or Dry periods respectively; (c) the frequency of ENSO year-types was less important than the overall rainfall surplus (or deficit) in La Niña (or El Niño) years within the Wet (or Dry) periods respectively; and (d) the timing of Wet and Dry periods was correlated with indices of quasi-decadal and inter-decadal variability in components (sea surface temperatures and atmospheric pressures) of the global climate system. Climatic risk assessment systems for grazing management at multi-year timescales are yet to be developed.

Queensland grazing industries operate in one of the world’s most variable climates and face enormous challenges to achieve profitability and sustainability. To assist grazing enterprises, the Queensland Government has developed an operational online information system – FORAGE, to facilitate best management practice for grazing land. The FORAGE system provides land managers with property-scale information relating to rainfall, ground cover, soil erodibility, land types, tree density, seasonal climate outlooks and pasture growth simulated using the GRASP grazing system model. This information is site-specific and tailored to facilitate on-ground management decisions common to Queensland grazing enterprises. The FORAGE system makes complex remotely-sensed data, information from a range of databases and pasture growth models more accessible and relevant to land managers. This paper describes the structure, resources (e.g. software, databases and models), information generating processes, delivery mechanisms and information products of the FORAGE system.

Queensland’s rangelands are an important source for Australia’s pastoral food production. However, they are subject to significant climate variability and will be under increasing pressure as the climate changes, potentially leading to loss of productivity. Pasture growth fluctuates greatly due to rainfall variability, which unfortunately is the climate variable with the largest uncertainties in future projections for northern and eastern Australia. This sensitivity study examines the effect of climate change and its interaction with soil fertility and trees on pasture and livestock production in Queensland. Nine climate change sensitivities were tested in various combinations; an increase in air temperatures by a median projected value of +3 °C, rainfall changes of -20 %, -10 % and +10 % and an increase of carbon dioxide concentrations to 700 ppm. The GRASP model was used to assess the responses of pasture growth, pasture quality and cattle liveweight change per head. The most arid areas in western and south-western Queensland were the most sensitive to changes in rainfall. In contrast, the tropical north was the most resilient region. Southern and south-eastern Queensland benefitted from higher air temperatures producing greater pasture growth, quality and liveweight gain per head by extending the growing season and reducing frost during the winter months. The presence of trees competing for water and nitrogen increased the sensitivity of pasture to climate change, especially at higher carbon dioxide levels and lower rainfall. Increased carbon dioxide enhanced pasture growth and mitigated rainfall reductions by improving the water use efficiency of the plants. Thus, a warmer climate may create new opportunities in the south and south-east, but a warmer and drier climate in the western regions of Queensland is likely to reduce pasture and livestock production.

An improved blended data method was developed for preparation and generation of solar radiation gridded datasets for SILO; Queensland Government database containing point and gridded daily climate data for Australia from 1890 till present designed for crop and pasture modelling. The new blended data method incorporates three sources of solar radiation data: radiometer measurements, sunshine duration, and cloud-cover observations. The new method converts all data sources to the percentage extra-terrestrial radiation using new conversion equations derived from the experimental data and thus the conversion tables previously used are now redundant. Comparison with satellite derived estimates shows that the blended data method has reduced bias compared to the previous method. The blended data method addresses the need for historical pre-satellite solar radiation gridded datasets for climate and agricultural modelling, model calibration, and computation of synthetic evaporation rates. The new method was developed for generation of solar radiation gridded datasets.It addresses the need for historical long-term pre-satellite solar radiation data.The method uses 3 sources of data: radiometer, sunshine hours, and cloud-cover.The method converts all data sources to the percentage extra-terrestrial radiation.Comparison with satellite estimates shows reduced bias.

It is widely recognised that defining trade-offs between greenhouse gas emissions using ‘emission equivalence’ based on global warming potentials (GWPs) referenced to carbon dioxide produces anomalous results when applied to methane. The short atmospheric lifetime of methane, compared to the timescales of CO2 uptake, leads to the greenhouse warming depending strongly on the temporal pattern of emission substitution.We argue that a more appropriate way to consider the relationship between the warming effects of methane and carbon dioxide is to define a ‘mixed metric’ that compares ongoing methane emissions (or reductions) to one-off emissions (or reductions) of carbon dioxide. Quantifying this approach, we propose that a one-off sequestration of 1t of carbon would offset an ongoing methane emission in the range 0.90–1.05kg CH4 per year. We present an example of how our approach would apply to rangeland cattle production, and consider the broader context of mitigation of climate change, noting the reverse trade-off would raise significant challenges in managing the risk of non-compliance.Our analysis is consistent with other approaches to addressing the criticisms of GWP-based emission equivalence, but provides a simpler and more robust approach while still achieving close equivalence of climate mitigation outcomes ranging over decadal to multi-century timescales.

Pasture biomass is an important quantity globally in livestock industries, carbon balances, and bushfire management. Quantitative estimates of pasture biomass or total standing dry matter (TSDM) at the field scale are much desired by land managers for land-resource management, forage budgeting, and conservation purposes. Estimates from optical satellite imagery alone tend to saturate in the cover-to-mass relationship and fail to differentiate standing dry matter from litter. X-band radar imagery was added to complement optical imagery with a structural component to improve TSDM estimates in rangelands. High quality paddock-scale field data from a northeastern Australian cattle grazing trial were used to establish a statistical TSDM model by integrating optical satellite image data from the Landsat sensor with observations from the TerraSAR-X (TSX) radar satellite. Data from the dry season of 2014 and the wet season of 2015 resulted in models with adjusted r2 of 0.81 in the dry season and 0.74 in the wet season. The respective models had a mean standard error of 332 kg/ha and 240 kg/ha. The wet and dry season conditions were different, largely due to changed overstorey vegetation conditions, but not greatly in a pasture ‘growth’ sense. A more robust combined-season model was established with an adjusted r2 of 0.76 and a mean standard error of 358 kg/ha. A clear improvement in the model performance could be demonstrated when integrating HH polarised TSX imagery with optical satellite image products.

The Queensland Government’s Long Paddock website has been redeveloped on Amazon Web Services cloud computing platform, to provide Australian rangelands and grazing communities (i.e. rural landholders, managers, pastoralists (graziers), researchers, advisors, students, consultants and extension providers) with easier access to seasonal climate and pasture condition information. The website provides free, tailored information and services to support management decisions to maximise productivity, while maintaining the natural resource base. For example, historical rainfall and pasture analyses (i.e. maps, posters and data) have been developed to assist in communicating the risk of multi-year droughts that are a feature of Queensland’s highly variable climate.

Interannual rainfall variability in Australia is a source of risk within agricultural industries. Insights into changes to rainfall and pasture-growth variabilities are essential to inform adaptation strategies for climate risk management within the grazing industry. We investigated shifts in rainfall and pasture-growth variabilities between the periods 1910–1960 and 1961–2010 for the pastoral zone in Australia. Rainfall variability was also assessed for the high-rainfall and wheat–sheep zones. An index of variability was calculated by using gridded rainfall and pasture-growth data for both periods. The percentage change was then calculated as the difference in variation between the two periods. Overall, the variability of annual rainfall has significantly increased (P < 0.01) between the two periods for the pastoral zone. Pastoral regions in the Northern Territory had the greatest increases in pasture-growth variability, with 62–85% of the area affected by a significant increase in variability. Between the periods 1910–1960 and 1961–2010 across the wheat–sheep zone, annual rainfall variability significantly decreased (P < 0.01), with 70% of the area having a negative change, whereas for the high-rainfall zone, the variability did not change significantly. Monitoring ongoing trends in rainfall and pasture-growth variability is important to inform strategic grazing management. Management practices to mitigate the impacts of increased variability in pastoral regions are discussed.

Context Feral pigs (Sus scrofa) are highly fecund, and populations can increase rapidly under favourable conditions. Population size can also fluctuate widely, driven largely by changes in juvenile mortality in response to food availability, but these relationships have only been explored on a limited number of sites and over short periods. Aims The present study aimed to investigate and quantify the numerical response of feral pig populations to changes in their food supply in north-eastern Australia. Methods Pig population densities were determined from aerial surveys conducted over a 21-year period on 10 regional blocks (~2000–6000 km2) throughout the Queensland rangelands. Densities were used to calculate annual exponential rates of increase (r), which were then corrected for anthropogenic mortality (baiting and commercial harvesting). Six proxy measures of annual food supply, including rainfall, pasture biomass and pasture growth (using the AussieGRASS model), were calculated for each survey block, and assessed as predictors of corrected r. The rates of increase predicted from the first half of the data series were then applied to initial population densities to estimate successive pig densities during the second period in each bioregion. Key results The most parsimonious model of the numerical response had parameters common to three bioregions, with rainfall in the 12 months between surveys being the best predictor variable. Modelled densities for each bioregion were a good fit to actual, observed densities. Relationships between r and each measure of food supply at the individual block level were inconsistent. Conclusions Using rainfall as a measure of food supply, the numerical response relationship provides a method for predicting the dynamics of feral pig populations at the bioregional scale. Predicting population dynamics at any one site using this relationship is less precise, suggesting that differences in landscape composition affect utilisation of resources supporting population growth. Implications The results from the present study could be used to predict feral pig population changes at the bioregional level, supplementing or reducing the need for more frequent, expensive population surveys. This improved ability to predict fluctuations in regional feral pig populations can help guide future management actions.

Global warming is likely to increase soil organic carbon decomposition, and thus CO2 release to the atmosphere, creating a positive feedback cycle. Inclusion of realistic estimates of soil black carbon in a climate model results in a decrease in soil CO2 emission in Australia by up to 24.4% following a 3 ∘C warming over 100 years, suggesting that black carbon reduces the strength of this feedback. Annual emissions of carbon dioxide from soil organic carbon are an order of magnitude greater than all anthropogenic carbon dioxide emissions taken together1. Global warming is likely to increase the decomposition of soil organic carbon, and thus the release of carbon dioxide from soils2,3,4,5, creating a positive feedback6,7,8,9. Current models of global climate change that recognize this soil carbon feedback are inaccurate if a larger fraction of soil organic carbon than postulated has a very slow decomposition rate. Here we show that by including realistic stocks of black carbon in prediction models, carbon dioxide emissions are reduced by 18.3 and 24.4% in two Australian savannah regions in response to a warming of 3 ∘C over 100 years1. This reduction in temperature sensitivity, and thus the magnitude of the positive feedback, results from the long mean residence time of black carbon, which we estimate to be approximately 1,300 and 2,600 years, respectively. The inclusion of black carbon in climate models is likely to require spatially explicit information about its distribution, given that the black carbon content of soils ranged from 0 to 82% of soil organic carbon in a continental-scale analysis of Australia. We conclude that accurate information about the distribution of black carbon in soils is important for projections of future climate change.

In this study, we sought to address the issue of how to derive an extended synthetic record of fire incidence and timing at regional scale that would be representative of a short remotely-sensed calibration record. We used annual rainfall and simulated annual ground stratum growth to develop multiple regression relationships for prediction of annual fire probability and proportion of late (August-November) fires from AVHRR NDVI fire footprint data across Australian tropical savannas. Relationships were examined using spatial averaging in moving windows varying from 3 X 3 to 61 X 61 pixels in size. Model fits as measured by R 2 improved as window size increased, but output layers became smoother and less representative of natural heterogeneity. A 25 X 25 pixel window was selected as the best compromise between model fit and smoothing. A 113-year synthetic record of annual fire probability and proportion of late fires was generated using the spatially explicit layers of model coefficients. The statistical properties of the synthetic fire probabilities were compared with those derived from the available fire footprint record, using a simple vegetation classification based on ground stratum type for spatial stratification. The two data sets showed a strong correspondence for both burned area and fire probability; spatial variation in mean and coefficient of variation of fire probability was representative of that observed in the historical record. There was significant temporal variation in the synthetic annual fire probability for different vegetation zones across the tropical savanna region for the full 113-year length of record. This simple approach could readily be applied to other areas of the world provided rainfall data are available and annual ground stratum growth can be simulated with a suitable model or estimated with remote sensing. Crown Copyright (c) 2005 Published by Elsevier Ltd. All rights reserved.

This paper uses a scenario analysis system - Range-ASSESS - to examine the potential for gains and losses of soil carbon in the Australian rangelands as affected by grazing and climate. The analysis involves a factorial examination of the effect of stocking rates and all possible 5-year historical climates between 1889 and 1999. The analysis also looks at the sensitivity of results to the method of calculation of safe carrying capacity, and to the thresholds used to calculate grazing and dryness indices that drive transitions in state and transition models. The analysis showed that different vegetation zones produced different responses to changes in stocking depending upon the spatial distribution of dryness index, nature of carbon state and transition model, rules governing transitions, and relative significance of soil carbon. At a stocking density equivalent to 100% of 1997 levels, the soil carbon loss from rangelands was about 400 Mt C in 40% of the 5-year periods using a sensitive growth deviation threshold to determine dryness index. If a less sensitive threshold was used, potential loss was reduced to about 200 Mt C. If the grazing pressure threshold for a grazing index of four is adjusted to a more generous level, then potential losses in the dry periods are substantially reduced. The analysis is intended to be indicative of a likely approximate outcome rather than a quantitative measure of system response. The results indicate that the interpretation of the effect of the drought-grazing pressure interaction on perennial plant survival, and consequent organic carbon input to soils, is a major source of uncertainty and a critical area for more experimental measurement.

Data from 57 permanent monitoring sites are used to document the growth in woody vegetation and estimate the carbon sink in 27Mha of eucalypt woodlands (savannas), contained withii c. 6OMha of grazed woodlands in Queensland (northeast Australia). The study sites are shown to be representative of the environment and structure of the eucalypt woodlands in the defined study area. Mean basal area increment for all live woody plants in 30 long-tenn sites, with an average initial basal area of 11.86 + 1.38 (SE)m2ha-', was 1.06m2ha-' over a mean 14years timeframe. The majority of the measurement period, commencing between 1982 and 1988, was characterized by belowaverage rainfall. The increase in live tree basal area was due primarily to growth of existing trees (3.1Zm2ha-'1 rather than establishment of new plants (0.25m2ha-I) qd was partly offset by death (2.31m2ha-'1. A simple but robust relationship between stand basal area and stand biomass of all woody species was developed for the eucalypt dominant woodlands. Analysis of above-ground carbon stocks in live and standing dead woody plants gave a mean net above-ground annual carbon increment for all 57 sites of 0.53 t C ha-' y-l, similar to values estimated elsewhere in world savannas. Published root: shoot ratios were used to infer C flux in woody mot systems on these sites. This results in an estimated sink in above- and below-ground biomass of 18MtCy-' over the eucalypt woodlands studied, and potentially up to 35MtCy-I if extended to all grazed woodlands in Queensland. It is suggested that introduction of livestock grazing and altered fire regimes have triggered the change in tree-grass dominance in these woodlands. Thus, change in carbon stocks in the grazed woodlands of Queensland is identified as an important component of human-induced greenhouse gas flux in Australia, equivalent in magnitude to c. 25% of the most recently published (1999) total estimated national net emissions. The latter inventory takes into account emissions from land clearing, but does not include the sink identified in the pment study. This sequestration also represents a small but significant contribution to the global terrestrial carbon sink.

A comprehensive archive of Australian rainfall and climate data has been constructed from ground-based observational data. Continuous, daily time step records have been constructed using spatial interpolation algorithms to estimate missing data. Datasets have been constructed for daily rainfall, maximum and minimum temperatures, evaporation, solar radiation and vapour pressure. Datasets are available for approximately 4600 locations across Australia, commencing in 1890 for rainfall and 1957 for climate variables. The datasets can be accessed on the Internet at http://www.dnr.qld.gov.au/silo. Interpolated surfaces have been computed on a regular 0.05° grid extending from latitude 10°S to 44°S and longitude 112°E to 154°E. A thin plate smoothing spline was used to interpolate daily climate variables, and ordinary kriging was used to interpolate daily and monthly rainfall. Independent cross validation has been used to analyse the temporal and spatial error of the interpolated data. An Internet based facility has been developed which allows database clients to interrogate the gridded surfaces at any desired location.

Increases in atmospheric concentrations of greenhouse gases such as carbon dioxide (CO2) are likely to impact on grazing industries through direct effects on plant growth and through possible changes in climate. Assessment of the likely direction and magnitude of these impacts requires development of appropriate modelling capacities linked with experimental work. This paper documents the adaptation of an existing soil–pasture–livestock model, GRASP, to simulate system responses to changes in CO2. The adapted model is then used to compare these responses under current climate and CO2 conditions with four possible future scenarios: (1) doubled CO2; (2) doubled CO2 and increased temperature; (3) as in the previous scenario but with a drier climate; and (4) as in (2) but with a wetter climate. These studies suggest that CO2 changes alone are likely to have beneficial effects, with increased pasture growth, increased and less variable liveweight gain, and increased ground cover. However, subsoil drainage is likely to increase. Growth responses to CO2 are likely to be greater in drier years than in wetter years partly due to nitrogen limitations in the soils of the region. Increases in temperature in combination with CO2 further increased animal production due to the increased number of growing days in the cooler months. The increased rainfall scenario had few additional positive effects but further increased subsoil drainage. In contrast, the drier scenario had reduced plant and animal production when compared with current conditions even though seasonal transpiration efficiency was increased by 20% due to increased CO2.

Australian agriculture is faced with the dilemma of increasing food production for a growing domestic and world population while decreasing environmental impacts and supporting the social and economic future of regional communities. The challenge for farmers is compounded by declining rates of productivity growth which have been linked to changes in climate and decreasing investment in agricultural research. The answer must lie in understanding the ecological functionality of landscapes and matching management of agricultural systems and use of natural resources to landscape capacity in a changing climate. A simplified mixed grain and livestock farm case study is used to illustrate the challenges of assessing the potential for shifts in land allocation between commodities to achieve sustainable intensification of nutrition production. This study highlights the risks associated with overly-simplistic solutions and the need for increased investment in research to inform the development of practical strategies for increasing food production in Australian agro-ecosystems while managing the impacts of climate change and addressing climate change mitigation policies.

Increasing atmospheric concentrations of ‘greenhouse gases’ are expected to result in global climatic changes over the next decades. Means of evaluating and reducing greenhouse gas emissions are being sought. In this study an existing simulation model of a tropical savanna woodland grazing system was adapted to account for greenhouse gas emissions. This approach may be able to be used in identifying ways to assess and limit emissions from other rangeland, agricultural and natural ecosystems.

SUMMARYExtensive grazing experiments were conducted over four summer breeding seasons in north-west Queensland between 1984 and 1989. Ewes in the last third of pregnancy were grazed on Mitchell grass (Astrebla spp.) pastures of varying forb (herbaceous plant other than a grass) content. Pastures of low forb content (F-) were attained by stocking paddocks heavily with wethers prior to the experiment, or by selecting paddocks which already contained pastures of low forb content. Pastures of high forb content (F+) were kept without animals prior to the experimental period. Pastures comprised a range of forb biomass (29–828 kg DM/ha) and percentage forbs in total biomass (3–49%). Lamb marking percentage was found to be dependent on the biomass of forbs and proportion of forbs in the pasture, in two experiments. Ewes which grazed F+ pastures had lower lamb marking percentages than those grazing F- pastures.Twenty pasture species collected during the experiments were analysed for the ratio of 13C: 12C and photosynthetic pathway was determined. Five forb and all three grass species had C4-dicarboxylic acid pathways, ten forbs had Calvin-C3 pathways and two forbs had crassulacean acid metabolism pathways.Estimates of the proportion of C3 and C4 species in the diet were determined by analysing the ratio of 13C:12C in faeces. The apparent high proportion of Calvin-C3 pathway forbs in the diet of ewes compared to the proportion in the total pasture biomass indicated that ewes preferentially select C3 forbs in the diet, although there was no dependence of lambing percentage on the estimated proportion of C3 forbs in the diet. Management strategies that may improve lambing percentage in the Mitchell grass areas of north-west Queensland are discussed.

Effective response by government and individuals to the risk of land degradation requires an understanding of regional climate variations and the impacts of climate and management on condition and productivity of land and vegetation resources. Analysis of past land degradation and climate variability provides some understanding of vulnerability to current and future climate changes and the information needs for more sustainable management. We describe experience in providing climate risk assessment information for managing for the risk of land degradation in north-eastern Australian arid and semi-arid regions used for extensive grazing. However, we note that information based on historical climate variability, which has been relied on in the past, will now also have to factor in the influence of human-induced climate change. Examples illustrate trends in climate for Australia over the past decade and the impacts on indicators of resource condition. The analysis highlights the benefits of insights into past trends and variability in rainfall and other climate variables based on extended historic databases. This understanding in turn supports more reliable regional climate projections and decision support information for governments and land managers to better manage the risk of land degradation now and in the future.

[1] We present data on soil organic carbon (SOC) inventory for 7050 soil cores collected from a wide range of environmental conditions throughout Australia. The data set is stratified over the spatial distribution of trees and grass to account for variability of SOC inventory with vegetation distribution. We model controls on SOC inventory using an index of water availability and mean annual temperature to represent the climatic control on the rate of C input into the SOC pool and decomposition of SOC, in addition to the fraction of soil particles

The possibility of trading greenhouse gas emission permits as a result of the Kyoto Protocol has spurred interest in developing land-based sinks for greenhouse gases. Extensive grazing lands that have the potential to develop substantial woody biomass are one obvious candidate for such activities. However, such activities need to consider the possible impacts on existing grazing and the possible impacts of continuing CO2 buildup in the atmosphere and resultant climate change. We used simulation models to investigate these issues in the mulga (Acacia aneura) woodlands of southwest Queensland. The simulation results suggest that this system can be managed to act as either a net source or a net sink of greenhouse gases under current climate and CO2 and under a range of global change scenarios. The key component in determining source or sink status is the management of the woody mulga. The most effective means of permanently increasing carbon stores and hence reducing net emissions is to exclude both burning and grazing. There are combinations of management regimes, such as excluding fire with light grazing, which, on average, allows productive grazing but transient carbon storage. The effects of increased CO2 on ecosystem carbon stores were unexpected. Carbon stores increased (7–17%) with doubling of CO2 only in those simulations where burning did not occur, but decreased when burnt. This occurred because the substantial increases in grass growth with doubling of CO2 (34–56%) enabled more fires, killing off the establishing cohorts needed to ensure continued carbon accumulation. On average, the doubling of atmospheric CO2 concentration increased grass growth by 44%, which is identical with mean literature values, suggesting that this result may be applicable in other ecosystems where fire has a similar function. A sensitivity analysis of the CO2 response of mulga showed only minor impacts. We discuss additional uncertainties and shortcomings. Keywords: Climate change, Carbon stores, Greenhouse emissions, Rangeland, Woodlands, Carbon dioxide, Impacts, Adaptation

Sub-daily rainfall intensity has a significant impact on runoff and erosion rates in northern Australian rangelands. However, it has been difficult to include sub-daily rainfall intensity in rangeland biophysical models using historical climate data due to the limited number of pluviograph stations with long-term records. In this paper a new empirical model (‘Temperature I15’ model) was developed to predict the daily maximum 15-min rainfall intensity (I15) using daily minimum and maximum temperature and daily rainfall totals from 12 selected pluviograph stations across Australia. The ‘Temperature I15’ model accounted for 46% (P

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

Grazing is a major land use in Australia’s rangelands. The ‘safe’ livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the ‘best estimates’ of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as ‘known uncertainties’ and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands (including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the ‘best estimate’ projections, in combination with appropriate responses to short-term (1–5 years) climate variability, would reduce the risk of resource degradation. Climate change projections – including changes in rainfall, temperature, carbon dioxide and other climatic variables – if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of fire, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3°C) was likely to result in a decrease in forage production for most rangeland locations (e.g. –21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (–33% or –9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3°C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the ‘best estimate’ of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

A spatially explicit state and transition model for assessing the interactive effects of grazing, fire and climate on carbon dynamics in Australian savannas is described. The model runs on a yearly time step. It is based on a sequential treatment of events within each year, involving, in order, growth of biomass, consumption of biomass by livestock and burning of the remaining fuel (growth minus consumption). The major drivers are 113 years of annual rainfall data, annual modelled rangeland growth, synthetic fire incidence and timing data, and data describing stocking rates in dry sheep equivalents. Baseline carbon stocks are derived from pre-settlement estimates from the VAST steady-state carbon model. State and transition models for nine vegetation zones define vegetation condition and consequent carbon stock. Change is mediated by key indices of driver variables such as grazing, growth and fire, a series of parameters and default thresholds, and a set of rules. The model is run for three 113-year spin-up cycles to establish a set of initial condition grids that represent a plausible synthetic current state. Sensitivity analyses on selected parameters and index thresholds showed that fire and growth thresholds were most important for woodland zones, and utilisation rates and degradation and recovery periods were most important for grassland zones. The model was used to examine a series of scenarios involving changes to grazing pressure and suppression of fire for different climate sequences. Changes to a few parameters enabled simulation of low and high levels of encroachment of woody weeds, and hence carbon accumulation, in the Astrebla (Mitchell) grasslands; and effective capture of the climate-induced variation in grassland condition, and hence potential for soil carbon loss, within Heteropogon spp.-dominated grasslands in northern Queensland. The scenario results suggest that this simple state and transition model with an annual time step provides a potentially useful and flexible scenario model framework for exploration of vegetation and consequent carbon dynamics of the Australian tropical savanna region.

A ‘multiple-constraints’ model-data assimilation scheme using a diverse range of data types offers the prospect of improved predictions of carbon and water budgets at regional scales. Global savannas, occupying more than 12% of total land area, are an economically and ecologically important biome but are relatively poorly covered by observations. In Australia, savannas are particularly poorly sampled across their extent, despite their amenity to ground-based measurement (largely intact vegetation, low relief and accessible canopies). In this paper, we describe the theoretical and practical requirements of integrating three types of data (ground-based observations, measurements of CO2/H2O fluxes and remote-sensing data) into a terrestrial carbon, water and energy budget model by using simulated observations for a hypothetical site of given climatic and vegetation conditions. The simulated data mimic specific errors, biases and uncertainties inherent in real data. Retrieval of model parameters and initial conditions by the assimilation scheme, using only one data type, led to poor representation of modelled plant-canopy production and ecosystem respiration fluxes because of errors and bias inherent in the underlying data. By combining two or more types of data, parameter retrieval was improved; however, the full compliment of data types was necessary before all measurement errors and biases in data were minimised. This demonstration illustrates the potential of these techniques to improve the performance of ecosystem biophysical models by examining consistency among datasets and thereby reducing uncertainty in model parameters and predictions. Furthermore, by using existing available data, it is possible to design field campaigns with a specified network design for sampling to maximise uncertainty reduction, given available funding. Application of these techniques will not only help fill knowledge gaps in the carbon and water dynamics of savannas but will result in better information for decision support systems to solve natural-resource management problems in this biome worldwide.

Land-use change, particularly clearing of forests for agriculture, has contributed significantly to the observed rise in atmospheric carbon dioxide concentration. Concern about the impacts on climate has led to efforts to monitor and curtail the rapid increase in concentrations of carbon dioxide and other greenhouse gases in the atmosphere. Internationally, much of the current focus is on the Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC). Although electing to not ratify the Protocol, Australia, as a party to the UNFCCC, reports on national greenhouse gas emissions, trends in emissions and abatement measures. In this paper we review the complex accounting rules for human activities affecting greenhouse gas fluxes in the terrestrial biosphere and explore implications and potential opportunities for managing carbon in the savanna ecosystems of northern Australia. Savannas in Australia are managed for grazing as well as for cultural and environmental values against a background of extreme climate variability and disturbance, notably fire. Methane from livestock and non-CO2 emissions from burning are important components of the total greenhouse gas emissions associated with management of savannas. International developments in carbon accounting for the terrestrial biosphere bring a requirement for better attribution of change in carbon stocks and more detailed and spatially explicit data on such characteristics of savanna ecosystems as fire regimes, production and type of fuel for burning, drivers of woody encroachment, rates of woody regrowth, stocking rates and grazing impacts. The benefits of improved biophysical information and of understanding the impacts on ecosystem function of natural factors and management options will extend beyond greenhouse accounting to better land management for multiple objectives.

Net primary production links the biosphere and the climate system through the global cycling of carbon, water and nutrients. Accurate quantification of net primary productivity (NPP) is therefore critical in understanding the response of the world’s ecosystems to global climate change, and how changes in ecosystems might themselves feed back to the climate system. Twelve model estimates of long-term annual NPP for the Australian continent were reviewed. These models varied considerably in the approaches adopted and the inputs required. The model estimates ranged 5-fold, from 0.67 to 3.31 Gt C y–1. Within-continent variation was similarly large, with most of the discrepancies occurring in the arid zone of Australia, which comprises most of the continent. It is also within this zone that empirical NPP data are most lacking. Comparison with a recent global-scale analysis of six dynamic global vegetation models showed a similar level of variability in continental total NPP, 0.38 to 2.85 Gt C y–1, and similar within-continent spatial variability. As a first tentative step towards model validation the twelve NPP estimates were compared with existing field measurements, although the ability to reach definitive conclusions was limited by insufficient data, and incompatibilities between the field-based observations and the model predictions. It was concluded that the current NPP-modelling capability falls short of the accuracy required for effective application in understanding the terrestrial biospheric implications of global atmospheric / climatic change. Potential methods that could be used in future work for improving modelled estimates of Australian continental NPP and their validation are discussed. These include increasing the spatial coverage of empirical NPP estimates within arid ecosystems, the use of existing high quality site data for more detailed model exploration, and a formal model inter-comparison using uniform driver datasets to investigate more intensively differences in model behaviour and assumptions.

This study examined the potential to simulate the quality, as indicated by nitrogen concentration, of the diet of sheep grazing the Mitchell and mulga grasslands of western Queensland. Development of this simulation capability will allow pasture growth and animal production models to be more easily coupled. Modifications and optimisation of an existing beef cattle diet selection model, in conjunction with a single sward pasture model, accounted for 69.1% (P < 0.001) and 41.9% (P < 0.001) of variation in sheep dietary nitrogen concentrations observed from grazing trials on Mitchell and mulga grasslands, respectively. Failure to simulate some of the higher recorded dietary nitrogen concentrations was probably associated with high forb content in the diet. Examination of the results indicated that development of pasture growth models which simulate major pasture species, or groups of species (e.g. perennial grasses, annual grasses, browse, forbs, legumes), would appear to be necessary before diet selection models will be better able to explain the variation in dietary quality observed in grazing animals.

This paper describes an innovative method, commonly referred to as ‘spider mapping’, that allows pasture biomass and related data to be collected over large areas in a timely and efficient manner. Spider mapping was developed initially to collect data to allow calibration and validation of a spatial and temporal pasture growth model operating across Queensland on a 5 km grid basis. Two field officers made over 220 000 estimates and collected about 1300 samples of pasture biomass between January 1994 and August 1995. A number of selected biomass samples were analysed for nitrogen, phosphorus and carbon content. In addition, data were also collected on foliage projective cover and tree basal area for a range of woodland communities and both variables compared with mean long-term Normalised Difference Vegetation Index values derived from a time series of National Oceanographic and Atmospheric Administration satellite imagery. Both variables were strongly related to the satellite data with overstorey foliage projective cover having the strongest non-linear correlation (r2 = 0.91). The method described here is currently being used in related work in the rangelands of New South Wales, South Australia, Western Australia and the Northern Territory.

The 160 million ha of grazing land in Queensland support approximately 10 million beef equivalents (9.8 million cattle and 10.7 million sheep) with treed and cleared native pastures as the major forage source. The complexity of these biophysical systems and their interaction with pasture and stock management, economic and social forces limits our ability to easily calculate the impact of climate change scenarios. We report the application of a systems approach in simulating the flow of plant dry matter and utilisation of forage by animals. Our review of available models highlighted the lack of suitable mechanistic models and the potential role of simple empirical relationships of utilisation and animal production derived from climatic and soil indices. Plausible climate change scenarios were evaluated by using a factorial of rainfall (f 10%) * 3260C temperature increase * doubling CO, in sensitivity studies at property, regional and State scales. Simulation of beef cattle liveweight gain at three locations in the Queensland black speargrass zone showed that a *lo% change in rainfall was magnified to be a f 15% change in animal production (liveweight gain per ha) depending on location, temperature and CO, change. Models of 'safe' carrying capacity were developed from property data and expert opinion. Climate change impacts on 'safe' carrying capacity varied considerably across the State depending on whether moisture, temperature or nutrients were the limiting factors. Without the effect of doubling CO,, warmer temperatures and +lo% changes in rainfall resulted in -35 to +70% changes in 'safe' carrying capacity depending on location. With the effect of doubling CO, included, the changes in 'safe' carrying capacity ranged from -12 to +115% across scenarios and locations. When aggregated to a whole-of-State carrying capacity, the combined effects of warmer temperature, doubling CO, and +lo% changes in rainfall resulted in 'safe' carrying capacity changes of +3 to +45% depending on rainfall scenario and location. A major finding of the sensitivity study was the potential importance of doubling CO, in mitigating or amplifying the effects of warmer temperatures and changes in rainfall. Field studies on the impact of CO, are therefore a high research priority. Keywords: climate change, Queensland, simulation, rangelands, beef production, cattle, carrying capacity, CO,, utilisation

Three distinctive savannas of north-east of fire are examined for each community. Utilization of Australia, originally dominated by unpalatable Eucalyptus these areas for beef and wool production is discussed and L'Herit spp., the valuable fodder Acacia aneura F. Muell. some approaches to predictive modelling of the systems are and Astrebla F. Muell. ex Benth. spp. grasslands are outlined. described. In each case an imbalance of woody and herbaceous plants now poses a threat to successful Key words. Savanna, tree-grass balance, Eucalyptus, pastoralism. Tree/shrub-grass relationships and the impact Acacia, Astrebla, Australia.